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Advancing risk management using new data techniques
The panel
- Irene Galperin, Senior adviser for financial services, InterSystems
- Nicole Königstein, Chief artificial intelligence officer and head of quantitative research, quantmate
- Peter Quell, Head of the portfolio analytics team for market and credit risk, DZ Bank
- Biljana Vujovic, Chief risk officer, Addiko Bank Montenegro
- Moderator: Sakshi Sharma, Americas content lead and editor, Risk.net
Risk management and data management have become central to the broader digitalisation efforts of financial institutions. A robust data strategy has an important role in supporting and enhancing risk management efforts.
This webinar shares best practices on how risk management can be improved using advanced modelling techniques and methodologies. It also discusses how best to optimise data-driven operating models, eliminate errors and provide consistent, reliable data for informed decision-making, as well as providing insights on how risk managers can use big data to improve risk modelling.
Key discussion topics:
- How risk managers can utilise big data to improve risk modelling
- What strategies can be implemented to establish a resilient data infrastructure, fostering connectivity and transparency among operational processes and leading to enhanced business insights
- The essential components that constitute a strong data foundation to facilitate smooth connectivity and transparency across operational functions
- Guaranteeing effortless access to, and integration of, data from diverse operational functions into broader processes to generate valuable insights
- Measures that should be implemented to ensure operations teams possess the required data literacy and analytical skills to leverage enhanced data capabilities for delivering business insights
- How financial firms can utilise technology and techniques to optimise their data-driven operating models
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